What is it about?
Modern markets have a large number of algorithmic traders are participants. This paper captures stylised aspects of their behaviour using public datasets from an exchange. When limit order markets are viewed in high resolution or ultra high frequency, the dependence between the market microstructure variables can help explain information flow in market. The information flow relates to how the traders bring information into the market. This could be through the price (spread), quantity or volume of shares in their quotes, arrival rates into the market or time of arrival, transactions. This paper describes the methodology of how the dependence between market microstructure variables can be investigated and used by market participants.
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Why is it important?
This research adds to the market microstructure toolbox. The methods currently used in market microstructure are not best suited to be employed in high resolution or ultra high frequency empirical investigation. VAR, ACD etc based methods are suitable for coarser analysis as they are designed under implicit assumption of equilibrium markets.
Perspectives
We have attempted to add to the microstructure toolbox in a limited way. We hope it helps market participants.
Sudhanshu Pani
Narsee Monjee Institute of Management Studies University
Read the Original
This page is a summary of: Investigating Intertrade Durations using Copulas: An Experiment with NASDAQ Data, Algorithmic Finance, August 2022, IOS Press,
DOI: 10.3233/af-200362.
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